Categorization based on user questionnaire

ABSTRACT

A customized questionnaire is generated for a content item, such as an eBook, audio file, video file, and so on. Upon an occurrence of predetermined event, the user is presented with the customized questionnaire soliciting responses to questions and/or rating evaluations relating to the content item. The responses may include reviews, ratings, recommendations of similar items, discussion topics, and other things. Information from the responses may be collected and associated with the content item to build a user-driven index.

BACKGROUND

A large and growing population of users is consuming increasing amountsof digital content, such as music, movies, audio books, electronicbooks, executables, and so on. These users employ various electronicaccess devices to consume such content. Among these access devices areelectronic book readers, cellular telephones, personal digitalassistants (PDAs), portable media players, tablet computers, netbooks,and the like. As more users consume content items electronically, newopportunities to interact with users are becoming available. Inparticular, feedback from users regarding content items offers valuableinformation that may be collected, organized and used to provide greaterdetail about the content items.

BRIEF DESCRIPTION OF THE DRAWINGS

The detailed description is set forth with reference to the accompanyingfigures. In the figures, the left-most digit(s) of a reference numberidentifies the figure in which the reference number first appears. Theuse of the same reference numbers in different figures indicates similaror identical items.

FIG. 1 is a block diagram of an illustrative architecture for monitoringconsumption of content items, detecting the occurrence of predeterminedevents, and obtaining responses from a user upon presentation of acustomized questionnaire.

FIG. 2 is a block diagram illustrating selected modules in an accessdevice of FIG. 1 that retrieves and presents content items and presentsa customized questionnaire.

FIG. 3 is a block diagram illustrating selected modules in a serversystem used to host an interaction and questionnaire service, as shownin the architecture of FIG. 1.

FIG. 4 shows an illustrative content database of FIG. 3, which may beused to store content items to be retrieved by the access devices and/orinformation about the content items.

FIG. 5 shows an illustrative content access database of FIG. 3, whichmay be used to store content access information.

FIG. 6 shows an illustrative user access profile database of FIG. 3,which may be used to store user access profiles.

FIG. 7 is a flow diagram of an illustrative process of solicitinginformation from a user of a content item with a customizedquestionnaire upon the occurrence of a predetermined event.

FIG. 8 shows an example user interface illustrating a customizedquestionnaire soliciting user input for an electronic book (“eBook”).

DETAILED DESCRIPTION

This disclosure describes an architecture and techniques in which theoccurrence of an event regarding a content item triggers a process ofsoliciting different types of information from the consumer/user of thecontent item with a questionnaire. Such information might includecomments, opinions, ratings, reviews, summaries, survey or quizresponses, discussion questions and topics, recommendations for similaritems, supplemental references, and so forth. Furthermore, the natureand extent of the consumer's interaction with the content item or othercontent items can be analyzed to evaluate the credibility of theconsumer with regard to the content item, and to validate or rate theresponses to the questionnaire provided by the consumer.

A content item may be essentially any form of electronic data that maybe consumed on a device, such as a digital book, electronic magazine,electronic newspaper, music, movie, and so on. A content item may alsobe composed of multiple smaller portions, such as units, chapters,sections, pages, tracks, episodes, parts, subdivisions, scenes,intervals, periods, modules, and so forth.

Content item consumers, referred to herein as users, may access andrender content items using a wide variety of access devices, such aselectronic book reader devices, cellular telephones, personal digitalassistants (PDAs), portable media players, tablet computers, and soforth. With the help of these devices, notifications or data pertainingto user progress through the content items may be collected, aggregated,and reported. This data may also indicate when a user has reached anidle point, completed a particular point in the content item or isorganizing the content item in relation to other content items. At thesepoints, additional information can be solicited from the user, relatingto the content item.

For example, when the content item is an electronic book (“eBook”) thereader may be asked to rate the eBook for adult content or readinglevel, provide a review or summary, indicate key concepts or the keyidea of the eBook, or provide any other sort of feedback. For instance,the user might also, or alternatively, be asked to provide additional,similar, complementary, or supplementary materials, such as discussionquestions and topics, or recommendations regarding other content itemsfor further reading or consumption. Furthermore, the reader may be askedto provide detailed feedback about the eBook for furthersub-categorization based on subject, style, genre, category, format,language, maturity rating, etc.

For discussion purposes, the architecture and techniques are describedin an online context where the content items are retrieved from remoteservers and completion information is gathered via an online service.However, the concepts described herein are also applicable in otherarchitectures, such as offline environments.

Content Access Information Architecture

FIG. 1 is an illustrative architecture 100 for monitoring userinteractions with a content item, subject to user consent of themonitoring. Monitoring in this manner facilitates the detection of userinteractions with content items, and also allows determining the natureand extent of the user's interaction with content items. Informationregarding the nature and extent of the user's interaction with a contentitem can be used to evaluate the credibility or authority of anyparticular user with respect to the content item, and to therebyvalidate, rate, or evaluate any information that the user suppliesregarding the content item. Also, the information can be used todetermine the occurrence of an event(s) that, when triggered,facilitates presenting the user with a questionnaire about the contentitem.

Users 102(1), . . . , 102(U) are part of a population of people thatutilize the architecture 100. The human users 102(1)-(U) consume a widevariety of content items, such as books, magazines, music, movies, andso on. As used herein, letters within parentheses, such as “(U)” or“(N)”, indicate any integer number greater than zero.

Each representative user 102(1), . . . , 102(U) employs one or morecorresponding electronic access devices 104(1), . . . , 104(N) to enableconsumption of one or more content items 106(1), . . . , 106(I). Forinstance, the user 102(1) uses an electronic book (“eBook”) readerdevice 104(1) to read digital textual material, such as electronicbooks, magazines, and the like. The user 102(U) employs a computer104(N) to enjoy any number of content items, such as watching a movie,listening to audio, or reading electronic text-based material. Whilethese example devices 104(1), . . . , 104(N) are shown for purposes ofillustration and discussion, it is noted that many other electronicdevices may be used, such as laptop computers, cellular telephones,portable media players, tablet computers, netbooks, notebooks, desktopcomputers, gaming consoles, DVD players, media centers, and the like.

The content items 106(1)-(I) are accessible from any of the accessdevices 104(1)-(N). The content items 106(1)-(I) may be stored locallyor accessible from a remote location over a network 108. As illustrated,the access devices 104(1)-(N) may connect to the network 108 to accessand retrieve the content items 106(1)-(I). The network 108 may be anytype of communication network, including the Internet, a local areanetwork, a wide area network, a wireless wide area network (WWAN), acable television network, a wireless network, a telephone network,combinations of the foregoing, etc. The network 108 allows communicativecoupling between the access devices 104(1)-(N) and remote servers, suchas network resource servers 110(1)-(S). Of particular note, individualones of the access devices 104(1)-(N), such as the eBook reader device104(1), may be equipped with a wireless communication interfaces thatallow communication with the servers 110(1)-(S) over a wireless network108. This allows information collected by the eBook reader device 104(1)(or other access devices) pertaining to consumption of content items106(1)-(I) to be transferred over the network 108 to the remote servers110(1), . . . , 110(S).

The network resource servers 110(1)-(S) may collectively have processingand storage capabilities to receive data from the access devices104(1)-(N), to process the data, and to respond to requests for analysisand reporting. The servers 110(1)-(S) may be embodied in any number ofways, including as a single server, a cluster of servers, a server farmor data center, and so forth, although other server architectures (e.g.,mainframe) may also be used.

The network resource servers 110(1)-(S) may be configured to host aninteraction and questionnaire service 112. The interaction andquestionnaire service 112 collects data pertaining to user interactionswith the content items as well as data associated with the content items106(1)-(I). In the illustrated embodiment, described in more detailbelow, the user interactions are recorded in data items referred to ascontent access events (CAEs).

The interaction and questionnaire service 112 may be configured toreceive CAEs from the access devices 104(1)-(N), or might otherwisecapture data indicative of an access device's attempts to access orconsume the content items 106(1)-(I). This information may be used togenerate user consumption metrics, derive completion information andstatistics, determine the occurrence of predetermined events, and/orevaluate the nature and extent of a user's interaction with anyparticular content item.

The content items 106(1)-(I) may be stored locally on the access devices104(1)-(N), or retrieved from a content item storage server 114 or othernetwork resources, which may be accessed via the network 108. Thecontent item storage server 114 may store or otherwise have access tocontent items that can be presented on the access devices 104(1)-(N).The server 114 may have processing and storage capabilities to receiverequests for content items 106(1)-(I) and to facilitate purchase and/ordelivery of those content items 106(1)-(I) to the access devices104(1)-(N). In some implementations, the server 114 may store thecontent items 106(1)-(4 although in other implementations, the server114 merely facilitates access to, purchase, and/or delivery of thosecontent items 106(1)-(I). The server 114 may be embodied in any numberof ways, including as a single server, a cluster of servers, a serverfarm or data center, and so forth, although other server architectures(e.g., mainframe) may also be used.

Alternatively, the content items 106(1)-(I) may be made available to theaccess devices 104(1)-(N) through offline mechanisms. For instance,content items 106(1)-(I) may be preloaded on the devices 104(1)-(N), orthe content items 106(1)-(I) may be stored on portable media that can beaccessed by the devices 104(1)-(N). For instance, electronic booksand/or magazines may be delivered on portable storage devices (e.g.,flash memory) that can be accessed and played by the access devices.Regardless of how the access devices 104(1)-(N) obtain the content items106(1)-(4 the interaction and questionnaire service 112 may collectcontent access events (CAEs) for the purpose of soliciting user feedbackvia a questionnaire.

In one example of this architecture in use, suppose the user 102(1) isreading contemporaneously several books on the eBook reader device104(1). At some point, the user 102(1) authorizes collection of accessdata by the interaction and questionnaire service 112 and, thereafter,accesses an eBook. As the user 102(1) turns the pages, highlightspassages, adds annotations, completes a chapter, or the like, data aboutuser's interaction with the content item is collected by the eBookreader device 104(1). This may include time spent on each page,annotations and their details, geographic location, motion duringaccess, moving the eBook to an archive file, and so forth.

At some point, the user 102(1) finishes reading a chapter of the eBookor the entire eBook itself, and the completion of the chapter and/oreBook is detected based on the user interaction data. Interaction andquestionnaire service 112, the access device 104(1), or both, may thensolicit different types of information from the user who just completedthe chapter and/or eBook. For instance, the service 112 and/or thedevice 104(1) may solicit this information from the user, such as via auser questionnaire 116 illustrated in FIG. 1.

Many types of information might be solicited as part of thequestionnaire 116, depending on the embodiment, particularcircumstances, and/or the type of content item or eBook that has justbeen completed. For example, the user 102(1) may be asked to answerquestions about the eBook, to rate the eBook based on suitability levelor reading difficulty, to provide a review or comments, or to indicatekey ideas or concepts found in the eBook. Other possibilities includerequesting specific types of recommendations, such as recommendations ofsimilar content items, referrals to other content items that mightdescribe complementary or contrary viewpoints, and references toexplanatory materials. The user 102(1) might also be requested toprovide supplemental materials, such as by authoring questions andtopics for discussion groups or questions for other users 102(U) to testtheir comprehension of the completed item. The user 102(1) may also beasked questions to test his or her own comprehension of the content item106(1). The questionnaire 116 can be formatted as questions, quizzes,tests, inquiries, and so forth.

The questionnaire 116 might be directed toward the subject matter of thecontent item 106(1), or about other things relating to the content item106(1) such as the formatting or presentation of the content item106(1). The user 102(1) could also be asked to evaluate likely targetaudiences or other peripheral information that might be useful toauthors and publishers. As such, the questionnaire 116 can be suppliedby the authors and/or publishers or other sources of the content item106(1). Questionnaire questions and/or rating evaluations could also begenerated or selected based on characteristics of the user's interactionwith the content item 106(1), such as which portions of the bookreceived the most attention, highlighting, or annotations by the user.

Questionnaire responses are entered by the user 102(1) and collected bythe access device 104(1) and/or the interaction and questionnaireservice 112. User responses to the questionnaire 116 can be input in theform of free text user input, menus, list boxes, check boxes, radiobuttons, sliders and so on. Any information solicited and obtained fromthe user 102(1) can be used to classify the content item 106(1) andconstruct a user-driven taxonomy of the content item 106(1) by alsoassociating information gathered from other users 102(U) about the samecontent item 106(1). The solicited information can also be subsequentlyshown to other users 102(U) at times when they are evaluating thecontent item 106(1). Information can also be used in determiningappropriate suggestions or recommendations for presentation to otherusers 102(U) who complete the content item 106(1). In addition,information can be offered to other users 102(U) as additional orsupplemental information when those users 102(U) consume or complete thecontent item 106(1). The presentation of this information is representedgenerally in FIG. 1 as a user recommendation 118.

When presenting information that has been obtained from users 102(1)-(U)in this manner, the information can be validated, weighted or ratedbased on the credibility of the user 102(U) who provided theinformation. This credibility, in turn, can be based on the nature andextent of the user's interaction with the content item 106(1), othercontent items 106(I) or an established reputation. For example, a reviewand rating value from a particular user 102(1) can be accompanied by acredibility or reputation score based on a variety of factors that mightinclude measurements of how fully the user 102(1) engaged or interactedwith the content item 106(1), a history of interactions with othersimilar content items 106(I), or independent indicia of reputation orqualifications such as subject matter expertise (e.g., a professor,professional, etc.).

CAEs can be monitored and analyzed to determine the nature and extent ofthe user's interaction with the content item 106(1). For example, theaverage time a user 102(1) viewed respective pages or chapters of acontent item 106(1) can be calculated. It might also be noted whether auser 102(1) actually read or consumed each page or portion of thecontent item 106(1), and how long it took the user 102(1) to consume theentire content item 106(1) from start to finish.

Example Access Device

FIG. 2 shows selected modules in an illustrative access device 104 fromFIG. 1. The access device 104 includes one or more processors 202configured to execute instructions and access data stored in memory 204.The memory 204 is representative of computer-readable storage that maybe implemented as volatile and/or non-volatile memory. The combinationof the processors 202 and the memory 204 embody operational logic thatis functional to perform the actions and processes that are attributedherein to access devices 104.

The content items 106(1)-(I) may be stored in the memory 204 (as shown)or otherwise accessed by the access device 104(1) for consumption. Forexample, an electronic book reader may render content of an electronicbook on a display for viewing, or an electronic player device may playaudible sounds from a music track for listening.

During access of the content items 106(1)-(4 the access device 104(1)generates content access events (CAEs) 206 that describe interactionswith the content items 106(1)-(I). The CAEs 206 may manifest as variousforms of data, such as access device status, flags, events, user inputs,etc. In some implementations, the CAEs 206 may be stored in the memory204 (as shown) and/or stored remotely (e.g., in memory of theinteraction and questionnaire service 112). While many CAEs 206 may beavailable, in some implementations only selected CAEs may be stored. Inone particular implementation (as illustrated in FIG. 2), the CAEs 206may include:

-   -   A content item identifier 208, such as title, identification        number, alphanumeric string, etc.    -   A power state 210 that indicates which components of the access        device 104 are active. For example, whether network interfaces        or radios are on, off, or in sleep mode during access of a        content item 106(1).    -   A load and/or unload state 212 to indicate whether a content        item 106(1) is loaded into the memory 204. The endpoints of the        load or unload may also be stored, as well as whether the user        102(1) retrieved a content item 106(1) from external storage and        stored in the memory 204, or vice versa. For example, whether a        content item(s) 106(1)-(I) is moved to an archive file or        deleted from memory 204.    -   A content item presentation state 214 to indicate when a content        item 106(1) or portion of a content item 106(1) is accessed by        the user 102(1) for display, playback, etc.    -   A presentation mode 216 that specifies various modes, such as        orientation of display, whether textual data was read using a        text-to-speech (TTS) feature, translated, etc.    -   A location 218 of the access device 104(1) when it accessed the        content item 106(1), including venue (e.g., airplane, night        club, etc.), specific geolocation, or both.    -   A position change 220 in the content item 106(1) during access.        For example, this might indicate turning to a specified page or        other navigation within a content item 106(1) or between        different content items 106(I).    -   Other input/output data 222 that may be captured and stored by        the access device 104(1). For example, accelerometer data may be        included to determine when the user 102(1) was in motion during        consumption of content.

The access device 104(1) further includes a set of input/output devicesgrouped within an input/output module 224, which may be used to providethe input/output data 222 or other information in the CAEs 206. Relevantinput/output devices include:

-   -   A real-time clock 226 to provide date and time. This clock may        be used to compute time-based CAE, such as when a content item        106(1) is accessed, or how long a user 102(1) remains in a        section of the content item 106(1).    -   One or more displays 228 to present content items 106(1)-(I)        visually to the user 102(1), and optionally act as an input        where a touch-sensitive display is used.    -   An audio device 230 to provide audio input and/or output of        content items 106(1)-(I).    -   A keyboard 232 to facilitate user input and may include pointing        devices such as a joystick, mouse, touch screen, control keys,        etc.    -   An accelerometer 234 to generate orientation and relative motion        input. For example, this may be used to determine orientation of        the access device 104(1) during consumption of a content item        106(1).    -   A global positioning system (GPS) 236 to enable determination of        geolocation, time data, velocity, etc. The GPS 236 may be used        to generate position or location-based CAEs that may be used to        help determine where user behavior occurs.    -   A wireless wide-area network (WWAN) 238 to provide a        communication connection to the network 108. A network interface        240 to facilitate a local wired or wireless communication        connection to the network 108, and may be used to identify and        track particular wireless networks to which the electronic        device connects.    -   Other sensors 242, which may include ambient light level        sensors, barometric pressure, temperature, user biometrics, etc.        Example Server

FIG. 3 shows selected modules 300 in the system of servers 110(1)-(S)used to host the interaction and questionnaire service 112, as shown inthe architecture of FIG. 1. The server system 110(1)-(S) includes theprocessors 302 that execute instructions and access data stored in amemory 304. The memory 304 implements a computer-readable storage mediathat may include, for example, random access memory (RAM), read-onlymemory (ROM), electrically erasable programmable read-only memory(EEPROM), flash memory or other solid-state memory technology, compactdisk read-only memory (CD-ROM), digital versatile disks (DVD) or otheroptical disk storage, magnetic cassettes, magnetic tape, magnetic diskstorage or other magnetic storage devices, or any other medium which canbe used to store the desired information and which can be accessed by aprocessor. The combination of processors 302 and memory 304 embodyoperational logic that is functional to perform the actions andprocesses that are attributed herein to the interaction andquestionnaire service 112.

Selected modules are shown stored in the memory 304. These modulesprovide the functionality to implement the interaction and questionnaireservice 112. One or more databases may reside in the memory 304. Adatabase management module 306 is configured to place data in, andretrieve data from, the databases. In this example, four databases areshown, including a content database 308, a content access database 310,a user access profile database 312, and a user database 314. Althoughshown as contained within the memory 304, these databases may alsoreside separately from the servers 110(1)-(S), but remain accessible tothem. The first three databases 308-312, and selected items of datastored therein, are discussed in more detail below with reference toFIGS. 4-6, respectively. The user database 314 may include informationsuch as user name, age, gender, social affiliations, geolocation,demographics, etc.

A content access event (CAE) collection module 316 may also be stored inmemory 304. The CAE collection module 316 is configured to gathercontent access event data from the access devices 104(1)-(N). Asdescribed above with respect to FIG. 2, the CAEs 206 includes accessdevice status, flags, events, and user inputs. For example, the CAEcollection module 316 may gather a set of CAEs 206 from the accessdevice 104(1) indicating that the item “To Serve Mankind” was lastdisplayed on screen two months ago for a period of ten minutes in alandscape presentation mode while on an airplane at an altitude of31,000 feet and speed of 513 miles per hour. Furthermore, the usernavigated through pages 57-64 during that time before switching to TTSpresentation. All of these factual data points may be captured as CAEs206.

A content access information (CAI) and usage metrics module 318 may bestored in the memory 304 and configured to generate CAI statistics fromthe CAE data collected by the CAE collection module 316 and to derivecontent usage metrics from the CAI and CAE data. The CAI is described inmore detail below with reference to FIG. 5. In another implementation,the access device 104 may process the CAEs 206 to produce the CAI or anintermediate data set, resulting in a smaller set of data fortransmission over network 108 and/or to reduce processing load on theinteraction and questionnaire service 112.

A questionnaire generation module 320 may be stored in the memory 304 togenerate user questionnaires 116 to be presented to and answered byusers 102(1)-(U) of particular content items 106(1)-(I) upon theoccurrence of predetermined events, such as, reaching an idle point(s),completion of a portion of those content items 106(1)-(4 completion ofthose content items 106(1)-(4 conclusion of annotations or highlights,at the conclusion of an allotted time period and so on. A user 102(1)may be deemed to have completed a content item 106(1) upon reaching thelast page of an eBook or upon navigating through the majority of thecontent item 106(1) and subsequently navigating away from the contentitem 106(1).

Questionnaires 116 may be the same for every content item 106(1)-(I) andevery user 102(1)-(U), or may be customized depending on the particularcontent item 106(1) that is activated and/or the particular user 102(1)who is interacting with the content item 106(1). Thus, upon theoccurrence of a predetermined event, like the conclusion of the contentitem 106(1), the user 102(1) may receive a different type ofquestionnaire 116 depending on the content item 106(1) or the type ofcontent item 106(1)-(I). Similarly, different users 102(1)-(U)completing a particular content item 106(1) may receive differentquestionnaires or types of questionnaires: Some users 102(1)-(U) mayreceive requests for reviews, while other users 1-2(1)-(U) receiverequests for providing ratings or recommendations. Furthermore, the typeof input available to receive responses may be specific to content items106(1)-(I) or users 102(1)-(U). For example, a certain user 102(1) mayonly be provided with radio buttons to respond to questionnaires. Thechoice of questionnaire 116 to be used with a particular user 102(1)with respect to a particular content item 106(1) can be preconfiguredfor each user 102(1) and/or content item 106(1), or chosen dynamicallyor automatically based on some algorithm in light of knowncharacteristics of the user 102(1) and/or content item 106(1).

A questionnaire results module 322 may also reside at the server system110 and reside within the memory 304. The questionnaire results module322 receives and stores the results of questionnaires. For example, itstores ratings, recommendations, reviews, and other information providedby users 102(1)-(U) as a result of answering questionnaires 116.Furthermore, the questionnaire results module 322 may extract andprocess specific information from the results of the questionnaires 116and forward them to be utilized in constructing a user driven index aspart of the content database 308, as further detailed below.

A validation module 324 in the memory 304 validates information providedby users 102(1)-(U) in response to questionnaires 116. Validation isperformed by evaluating the nature and extent of a user's interaction102(1) with the content item 106(1). Higher or more extensiveinteraction results in a higher degree of validation being associatedwith the user's input. Generally, each set of information resulting froma particular questionnaire 116 is associated with a validation score orrating. The nature and extent of the user's interaction with the contentitem 106(1) is evaluated based on an analysis of CAE's associated withthe user's consumption of the content item 106(1). Furthermore,validation can be performed by evaluating the nature and extent of auser's past interaction with other customized questionnaires 116. Forexample, a user 102(1) with a history of responding to questionnaires116 presented to the user while engaged with previous content items106(1)-(I) can have a higher degree of validation associated with theuser's current input for a customized questionnaire 116. Furthermore,the quality, characteristics and features of the user's input can alsocontribute to the degree of validation associated with the input asfurther detailed below.

A report generation module 326 is configured to transform thequestionnaire results and associated validation scores into selectedformats and representations that may be used in conjunction with contentitem descriptions, listings of content items, and other data that may bepresented to other users 102(U). For example, questionnaire results mayaccompany content item descriptions in an online storefront. If desired,a user 102(1) contemplating the purchase of a particular content item106(1) may look at reviews or ratings supplied by other users 102(U) asa result of questionnaires 116. Alternatively, certain types ofquestionnaire information, such as further recommendations or discussionquestions, may be presented to other users 102(U) when they interactwith and/or complete a content item 106(1).

The server system 110 may also be equipped with a network interface 328,which provides a local wired or wireless communication connection to thenetwork 108. The network interface 328 allows for communication with theaccess devices 104 via the network 108, as shown in FIG. 1.

An incentive module 330 is configured to generate and present incentivesto users 102(1)-(U) for providing responses solicited by thequestionnaire 116. The incentives can be monetary or non-monetary. Forexample, monetary incentives can be in the form of discounts on thepurchase of available content items 106(1)-(I). Non-monetary incentivescan take the form of reward points to be accumulated and redeemed toobtain content items 106(1)-(I) or other goods/services. In anotherexample, the non-monetary incentive may be in the form of obtainingstatus as a credible and respected reviewer. Obtaining such status canpermit the user 102(1) to access further rewards and privileges reservedfor users 102(1)-(U) possessing such standing.

FIG. 4 shows the illustrative content database 308 maintained at, oraccessible by, the servers 110(1)-(S) of FIG. 3. The content database308 is configured to contain content item information 402, whichincludes essentially any information pertaining to content items106(1)-(I) that a user 102(1) may wish to access and consume. Asmentioned previously, information from responses to questionnaires 116may be used to populate the content item information 402. For discussionpurposes, the content item information 402 may include the following:

-   -   Content item identification 404, such as title, identification        number, invariant reference number, etc.    -   Content item format 406, such as whether the content item 106(1)        is available as a book, audio, video, executable program, etc.    -   Genre of content item 408, such as mystery, science fiction,        biography, horror, reference, game, utility, etc. For example,        responses by a user 102(1) to a questionnaire 116 can provide        broad categories associated with the content item 102(1) such as        novel, textbook, history, biography, compilation, and so on.        Furthermore, user responses can further subcategorize the        content item 106(1) into granular details such as historical,        first person novel, adapted to a movie, deceased author, etc.    -   Complexity of content item 410. For example, in textual content        items 106(1), complexity may be determined based on a measure of        readability. Examples of readability measurement include a        Flesch-Kincaid Readability score, assessment of reading grade        level (i.e. preschool—college level), the mean and variance of        reading velocity, frequency of dictionary look-ups, or other        metrics which may be used to ascertain the relative intricacy of        the content item 106(1), or a combination of these measurements.        Complexity of other types of content items 106(I) may be        determined by other suitable metrics. For example, a musical        piece may have complexity determined by spectral analysis, or an        executable may have complexity determined by the size of the        code and number of possible user inputs during use. In another        implementation, complexity may be derived from user feedback.    -   Related works 412, such as music tracks found in the same album,        books in a series, movies by the same director, etc. Moreover,        user responses can further identify item(s) related to a        particular content item across different forms of media (e.g.        music, video, audio, etc.).    -   Title authority 414, which links or associates multiple        instances of the same work or set of works (e.g., different        formats or imprints of the same title).    -   Sales data 416, such as historical sales data, quantities        sold/licensed, profit margin, returns, etc.    -   Bibliographic data 418, such as author, artist, publisher,        edition, length, catalog number, etc.    -   Suitability of content item 420, such as the degree of violence,        nudity, sexual content, profanity, drugs, adult themes, etc. For        example, a graphic novel about serial killers can be identified        as possessing material not suitable for younger users or those        that may be sensitive to the subject matter. Suitability can be        expressed in terms of generally accepted ratings system such as        for movies (e.g. G, PG, PG-13, R, NC-17, etc.).

FIG. 5 shows the illustrative content access database 310 of FIG. 3,which is configured to contain content access information 502. Thecontent access information 502 may be derived from CAEs 206. Fordiscussion purposes, the content access information 502 may include thefollowing:

-   -   A user identification 504, allowing association of a particular        user with a particular set of content access information.    -   A content item identification 404, as described above.    -   An elapsed time since last access 506. In one implementation,        access may be defined as a user 102(1) interacting with the        content item 106(1) such that minimum duration thresholds are        exceeded. For example, access to a book may be defined as two        page turns in over ten seconds, to minimize erroneous data from        inadvertent interaction such as incorrectly selecting a book.    -   A total access time of the content item by the user 508.    -   An access velocity 510 (a rate of item consumption per unit        time) by time and/or position in the content item 106(1). For        example, the user 102(1) read 113 words per minute in chapter 3,        or the user 102(1) read page 15 in 54 seconds.    -   An access duration by time period 512. For example, the user        102(1) read for 37 minutes on April 1. This access duration by        time period 512 may be for a single content item 106(1) or for        all content items 106(1)-(I) accessed by a user 102(1) during a        specified time period selected.    -   An access duration by portion 514. For example, this data might        indicate how long the user 102(1) spent on a particular page,        chapter, section, or other portion of a content item 106(1).    -   A frequency of access 516. For example, how often a content item        106(1) or portion of a content item 106(1) is accessed.    -   A position in content of last access 518. For example, the        position in content of the last access was 237 words into        chapter 5.    -   A data item 520 pertaining to the path of content item 106(1)        access by user 102(1). For example, a path may track as the user        102(1) skips from chapter 1 to chapter 5, then back to chapter        3, and then switched to another book, and finally returned to        read chapter 7.    -   A location during access 522. Locations include venues such as        airplanes, night clubs, restaurants, etc., specific geolocation        such as 48.93861° N 119.435° W, or both. For example, the user        102(1) accessed content item 106(1) from access device 104(1)        which was located in Trafalgar Square.    -   An initial access of the content item 524. Specifically, whether        the initial access was self-initiated or the result of a        personal or automated recommendation to a user 102(1).    -   Data derived from other sensor inputs 526, such as an        accelerometer or ambient light sensor. For example,        accelerometer input may provide data indicating the user 102(1)        reads while walking. In another example, ambient light input in        conjunction with other CAI may indicate that users 102(1)-(U)        have a greater rate of abandonment when reading in low light        levels. In yet another example, deleting or moving a content        item 106(1) to an archive file or another inactive section    -   Completion information 528, indicating whether a specific        portion of the content item 106(1) has been completed or whether        the content item 106(1) itself has been completed. Completion of        a content item 106(1) may be evaluated using various different        criteria, such as whether the user 102(1) has reached the last        page of an eBook or has sequentially navigated through a        majority of a content item 106(1).    -   Annotation information 530, such as annotations made by users        102(1)-(U). Annotations can be in the form of notes, highlights,        bookmarks, etc.

FIG. 6 shows the illustrative user access profile database 312 of FIG.3, which is configured to contain a user access profile 602. The useraccess profile 602 may include a variety of information about the user102(1) and their preferences. For discussion purposes, the user accessprofile 602 may include user preferences 604 that have been explicitlyentered by a user 102(1) or derived from other user data. Further, suchpreferences 604 may be inferred over time from the user's behavior, orfrom examining behavior of other users 102(U) who are deemed to besimilar to the user 102(1). These user preferences 604 may include thefollowing:

-   -   A preferred maximum complexity level 606. For example, the user        102(1) prefers content items not exceeding a 7^(th) grade        reading level.    -   A preferred content item format 608. For example, the user        102(1) prefers to use the text-to-speech function, largest font        available, etc.    -   A preferred genre of content items 610, such as mystery, science        fiction, biography, horror, reference, etc.    -   A preferred type of content item 612, such as text, audio,        video, etc.

The user access profile 602 may also include CAI derived data 614 thathas been derived from the CAEs 206. For discussion purposes, the CAIderived data 614 may include the following:

-   -   A consumption access velocity/complexity matrix 616. For        example, a user (or group of users) 102(1)-(U) may have a matrix        describing the relationship between access velocity and        complexity. Thus, the user (or group of users) 102(1)-(U) may        exhibit a high access velocity (such as 350 words per minute)        with low complexity content items 106(1)-(I) such as a brochure,        but may exhibit a low access velocity (such as 100 words per        minute) for a high complexity content item 106(1)-(I) such as a        math treatise.    -   An abandonment characteristics matrix 618. This matrix would        characterize a relationship for a user (or group of users)        102(1)-(U) between consumption statistics and abandonment of the        content item 106(1), including deleting or archiving the content        item 106(1).    -   A completion characteristics matrix 620. This matrix would        characterize a relationship for a user (or group of users)        102(1)-(U) between consumption statistics and completion of the        content item 106(1).    -   A time/location consumption matrix 622 similar to the previous        matrices. The time/location consumption matrix 622 establishes a        relationship between clock time and location (such as venue or        geolocation) and consumption of content 106(1)-(I). For example,        a user 102(1) may have the most uninterrupted time to read from        7 a.m. to 8 a.m. while on the train.    -   A best reading time of day 624. For example, a user 102(1) may        exhibit a personal highest average access velocity during 8 a.m.        and 9 a.m. local time.        User Interaction

FIG. 7 shows an illustrative process 700 of monitoring user interactionwith content items 106(1)-(I) to determine the occurrence of apredetermined event and presenting customized questionnaires to solicitresponses to questions or rating evaluations provided therein. Theprocess 700 is illustrated as a collection of blocks in a logical flowgraph, which represent a sequence of operations or operational logicthat can be implemented in hardware, software, or a combination thereof.In the context of software, the blocks represent computer-executableinstructions stored on one or more computer-readable storage media that,when executed by one or more processors, perform the recited operations.Generally, computer-executable instructions include routines, programs,objects, components, data structures, and the like that performparticular functions or implement particular abstract data types. Unlessstated otherwise, the order in which the operations are described is notintended to be construed as a limitation, and any number of thedescribed blocks can be combined in any order and/or in parallel toimplement the process. For discussion purposes, the process will bedescribed in the context of the architecture of FIGS. 1-6, in which theillustrated operations are performed under control of a device such asan electronic book reader device, which stores and executes instructionsthat implement the described functionality.

At block 702, a customized questionnaire is generated for a particularcontent item rendered for consumption by a user. The customizedquestionnaire can comprise of at least one question and/or ratingevaluation based at least in part on the particular content item toclassify the content item. Many content items have sequential portions,such as pages, chapters, episodes, tracks, scenes, etc., that arerendered in a natural order. Content items may be obtained or purchasedfrom an electronic catalog and rendered in various ways, including bydisplaying content, playing audio or video content, or otherwiseconverting the item into a human perceptible form. In many cases, theuser is also allowed to navigate arbitrarily within or between portionsof the content item. As mentioned previously, the customizedquestionnaire may be supplied by a publisher, author or other source ofthe content items.

The customized questionnaire may comprise of questions or ratingevaluations soliciting information from the user regarding the contentitem. The solicitation might include posing one or more questionsregarding the content item or presenting one or more of a variety ofdifferent requests, such as requests for the items referenced by numeral716 in FIG. 7, which include categorizations, tags, surveys, reviews,ratings, questions, etc. The user might be asked to provide originalreviews, ratings, recommendations for similar items, discussion topics,discussion questions, audio/video commentaries, summaries, key topics,contrary resources, supplementary resources, and other types ofinformation relating to the content item. Additionally, the user mightbe asked to identify other users who might enjoy the content item, andmight be given the opportunity to gift or loan the content item tospecified other users.

At block 704, the customized questionnaire is presented upon theoccurrence of a predetermined event. The customized questionnaire may bepresented as an interactive pop-up item when a user completes aparticular portion of the content item, the entire content item orprovides an indication that the user will not return to the content itemin the near future. Alternatively, the user might be linked to adifferent page or website containing one or more requests forinformation. As detailed previously, the predetermined event cancorrespond to the conclusion of a page, chapter, content, annotation orhighlight associated with the content item. Moreover, the expiration ofan allotted amount of time or the manipulation of the content item onthe device may also comply. Specifically, if a reasonable amount of timehas passed between a user's handling of a content item, the user may besolicited for information underlying the reasons for the delay. Inanother example, if a user attempts to delete or move a content item toan archive file, a customized questionnaire may be presented to obtainfeedback from the user as to the motivation for the acts of the user. Ingeneral, the customized questionnaire may be presented at a point intime that is not overly disruptive to the user's interaction with thecontent item. In the context of eBooks, for example, the following aresome examples of the occurrence of predetermined events:

-   -   The user reaches the last page of an eBook.    -   The user navigates essentially through the majority or a        threshold amount of the eBook, concluding a page near the end of        the book.    -   The user navigates sequentially through the last few pages of an        eBook, including the last page.    -   The user reaches the last page of an eBook and navigates away        from the eBook.    -   The user reaches the last page of an eBook and remains there for        an unusually long time.    -   The user initiates steps to delete an eBook from memory or move        it to an archive file.

For other content items, analogous processes of monitoring userinteraction through the content item may be used.

In some cases, such as when a content item has an appendix or othersecondary matter following the primary content, the “end” of the contentitem may be ambiguous. This can be dealt with in different ways,depending upon implementation or upon preferences specified by a user.For example, some implementations may deem completion of a book uponreaching the end of the primary content, regardless of whether appendedsecondary matter has been consumed. Other embodiments may not deem acontent item as being completed unless the user has navigated to the endof any secondary matter.

In some embodiments, the user may be prompted to confirm completion, andcompletion may be deemed to have happened only upon user confirmation orsome other explicit user indication.

Note that different embodiments may use different mechanisms fordetecting the occurrence of predetermined events associated with auser's interaction with content items. One embodiment might includecomprehensive user activity monitoring by receiving CAEs, as describedabove, in which the occurrence of a predetermined event, such as thecompletion of the content item, is inferred or detected based on variousdifferent types of user activity information. Other embodiments may beimplemented without such comprehensive user activity monitoring. Forexample, a particular reader device or program might be configured tosimply notify or report when a user has reached the end of the contentitem or has navigated away from the end of the content item.

At block 706, an incentive may be offered to encourage the user toprovide responses to the customized questionnaire. As previouslydetailed, the incentive may be monetary or non-monetary, with the amountof the incentive offered corresponding to the degree of completion ofthe customized questionnaire. In another implementation, the amount ofthe incentive can correspond directly to the content item. For example,a greater incentive can be offered to a user for providing responses toa customized questionnaire for an eBook with a certain amount of content(e.g., an amount of content that is analogous to a length of a physicalbook that is over 400 pages in length) vis-à-vis an eBook with lesscontent (e.g., an amount of content that is analogous to a length of aphysical book that is less than 100 pages in length).

At block 708, responses to the customized questionnaire are received. Insome embodiments, the responses from the user can be in the form of freetext input, selections from drop-down menus, list boxes, check boxes,radio buttons, sliders or any combination thereof. The responses mightalso comprise answers to questions or quizzes, ratings, reviews,recommendations for similar items, discussion topics, discussionquestions, commentary, summaries, key topics, contrary resources,supplementary resources or materials, and so forth. The information maybe entered directly, or might be provided by way of links or references.

Responses may also be supplied at varying times. In one instance, a usermay partially provide responses to a questionnaire, may interact with adifferent content item on the device, and later go back to the partiallycompleted questionnaire to respond to further questions or inquiries.

At block 710, the responses are weighted based in part on acharacteristic of the user. This can be accomplished by determining andassigning a credibility score or other indication of usefulness ortrustworthiness. As described above, CAEs can be evaluated to determinecharacteristics of the user's interaction with the content item prior toits completion, such as whether the user read every page of a book,viewed every chapter of a movie, listened to the entirety of song oralbum, and so forth. The CAEs may also contain other informationrelevant to the user's engagement with the content item, such ascharacteristics of annotations made by the user, the number of portionsor pages viewed or rendered, the length of time that individual pages orportions were viewed or rendered, the length of time that the contentitem as a whole was viewed or rendered, the elapsed time from startingthe content item to completing it, whether the content item was consumedin a single uninterrupted session, and other characteristics of theuser's interaction with the content item. These factors and others canbe weighted and combined to form a validity or credibility score thatindicates the estimated validity, value, or trustworthiness of theinformation received from the user.

In another embodiment, the characteristic of the user may comprise ahistory of providing responses to past questionnaires or the quality andextent of the user's responses. The characteristic may also comprisequalities inherent to the user. For example, responses to aquestionnaire obtained from a professor teaching microbiology at auniversity regarding a book about food-borne illnesses can be weighedfavorably compared to responses from others for the same book.

At block 712, the responses are associated with the content item. Asmentioned above, the content database 308 is configured to containcontent item information 402. The information in the responses can beincorporated to supplement or enhance the data stored in the contentdatabase 308. For example, a user provides a suitability rating of “R”for a book about terrorism due to the book's inclusion of graphicdepictions of violence and strong language not appropriate for thoseunder the age of 17. The “R” rating can be associated with the book andincluded in the content item information 402, specifically as part ofthe suitability of content item 420. After collecting and associatinginformation from responses to the customized questionnaires, theinformation can be used to establish and maintain a user-driven index ortaxonomy of the content items to determine, for example, how one contentitem may relate to one or more other content items.

At block 714, recommendations may be generated based on the user-drivenindex incorporating information derived from the responses for thecustomized questionnaires and the usage metrics detailed above. As oneexample, recommendations may be made to consume other content items. Forinstance, the service may determine other content items that seemsuitable for a reader who exhibits a certain reading rate or subjectmatter complexity level. As still another example, recommendations maysuggest one or more services to try. For instance, suppose an adult userexhibits a below normal reading rate. In such situations, arecommendation may be made to seek out a reading serviced for speedreading techniques. Recommendations for activities may also be generatedbased on content usage metrics and the responses for the customizedquestionnaires. For instance, if the user consistently accesses contentitems pertaining to mountain biking, a recommendation may be made tojoin a local mountain biking club or register for an upcoming mountainbiking event.

In another example, recommendations may purposefully not include certaincontent items in view of the users and/or the responses for the contentitems. For instance, content items that are associated with suitabilityratings of PG-13 or higher may not be included to users identified asminors or to users who seek to avoid such content items.

Validity or credibility scores may be displayed along with thecorresponding information supplied by the users. Alternatively,recommendations may be filtered based on credibility scores. Forexample, it might be useful in some situations to display only thatrecommendation that is associated with higher credibility scores. Inother situations, composite recommendations about a particular contentitem might be compiled using only the user input that is associated withhigher credibility scores, or by weighting user input depending on itscredibility scores.

FIG. 8 shows the eBook reader device 104(1) while presenting an exampleof a customized questionnaire. This example illustrates completion of aneBook 802 entitled “Romeo and Juliet”. Upon the occurrence of apredetermined event, the reader device 104(1) displays a pop-up oroverlay customized questionnaire pane 804. The customized questionnairepane 804 can contain questions, requests, rating evaluations, multiplechoice problems, quizzes, tests, etc., as described above.

In this example, the questionnaire 804 contains a request 806 for theuser to rate the appropriate reading level for the eBook 802 in the formof a list box 808, a question 810 asking the user to rate thesuitability of the content of the book in the form of radio buttons 812corresponding to a widely familiar ratings scheme, a question 814 askingthe user to categorize the book in the form of a text entry box 816, aquestion 818 to identify another similar book, and a request 820 for theuser to identify other content items that the user would recommend forothers who enjoyed this book. A user may provide answers to one or moreof the questionnaire items and submit them by selecting a control 822,which is labeled “Submit”. Alternatively, the user may ignore thequestionnaire by selecting a “Close” control 824.

In some instance, a questionnaire may include multiple questions orrequests, presented in a series of individual panes 804. Alternatively,multiple questions or rating evaluation can be presented in a singlepane as shown, or a questionnaire might consist of only a singlequestion or rating evaluation.

CONCLUSION

Although the subject matter has been described in language specific tostructural features and/or methodological acts, it is to be understoodthat the subject matter defined in the appended claims is notnecessarily limited to the specific features or acts described. Rather,the specific features and acts are disclosed as exemplary forms ofimplementing the claims.

What is claimed is:
 1. A computer-implemented method comprising: undercontrol of one or more computer systems configured with executableinstructions, receiving an indication of a user interaction, via a userdevice, with an electronic book; identifying, from a user profile, anassociation between a genre of electronic books and content access event(CAE) data, the CAE data including at least one of a particular time ofday or a particular location; determining, based at least in part on theindication, an occurrence of an event that is associated with at least aportion of the CAE data; determining a rate of abandonment of electronicbooks associated with an ambient light intensity that is equal to orbelow a threshold value; determining, based at least partly on theindication, that a current ambient light intensity received by the userdevice is at or below the threshold value; generating a customizedquestionnaire associated with the electronic book that includes at leastone question based at least in part on the genre of electronic books,the at least one question including a question associated with anabandonment of the electronic book; sending the customized questionnaireto the user device upon an occurrence of a predetermined event tosolicit a response to the at least one question; receiving the responsefrom the user device; associating the response with the electronic bookto build or update a user-driven index of a catalog; and generating adifferent customized questionnaire for the electronic book, thedifferent customized questionnaire including at least one differentquestion based at least in part on the response.
 2. Thecomputer-implemented method of claim 1, further comprising: causingdisplay of a user interface on the user device, the user interfaceincluding one or more of free text user input, menus, list boxes, checkboxes, radio buttons, or sliders to receive the response.
 3. Thecomputer-implemented method of claim 1, further comprising: detecting anexpiration of an allotted amount of time after a commencement of theuser interaction, and wherein the predetermined event is based at leastat least in part on the expiration of the allotted amount of time. 4.The computer-implemented method of claim 1, further comprising:detecting that the electronic book is being associated with at least oneother electronic book in a collection of electronic books on the userdevice, and wherein the user interaction is based at least in part ondetecting that the electronic book is being associated.
 5. Thecomputer-implemented method of claim 1, wherein the indication of theuser interaction is a first indication, and further comprising:receiving a second indication, via the user device, of an annotation tobe associated with a portion of the electronic book, and wherein thecustomized questionnaire includes an additional question that solicits arecommendation for similar items based in part on the annotationassociated with the portion of the electronic book.
 6. Thecomputer-implemented method of claim 1, further comprising: causingdisplay of at least one additional question within the customizedquestionnaire that solicits information regarding a category of theelectronic book, a subject of the electronic book, a style of theelectronic book, a format of the electronic book, or a language of theelectronic book.
 7. The computer-implemented method of claim 1, furthercomprising: causing display of at least one additional question that isassociated with assessing a reading level of the electronic book.
 8. Thecomputer-implemented method of claim 1, further comprising weighting theresponse based in part on a characteristic of the user profileassociated with the user device.
 9. The computer-implemented method ofclaim 8, further comprising: identifying, from the user profile,previous responses to other customized questionnaires, and wherein thecharacteristic is based at least in part on the previous responses. 10.The computer-implemented method of claim 1, further comprising providingan incentive to provide the response to the customized questionnaire.11. The computer-implemented method of claim 1, further comprisinggenerating a recommendation based at least in part on the user-drivenindex.
 12. A computer-implemented method comprising: under control ofone or more computer systems configured with executable instructions,receiving, from a user device, an indication of a user interaction, theuser interaction including a purchase of a content item of a pluralityof content items; determining a rate of abandonment of content itemsassociated with an ambient light intensity that is equal to or below athreshold value; determining, based at least partly on the indication,that a current ambient light intensity received by the user device is ator below the threshold value; generating a customized questionnaire forthe content item of the plurality of content items; causing display ofthe customized questionnaire on the user device based at least in parton the indication, the customized questionnaire to solicit a response toat least one question that is associated with an abandonment of thecontent item; receiving, via the user device, the response; associatingthe response with the content item to build or update a user-drivenindex comprising the plurality of content items; and generating adifferent customized questionnaire for the content item that includes atleast one different question based at least in part on the response, anda recommendation for at least one activity.
 13. The computer-implementedmethod of claim 12, further comprising: causing display of at least oneadditional question within the customized questionnaire that solicits arequest for items that are identified as similar to at least one of theplurality of content items.
 14. The computer-implemented method of claim12, further comprising: causing display of at least one additionalquestion that assesses an education level or reading level commensuratewith at least one of the plurality of content items.
 15. Thecomputer-implemented method of claim 12, further comprising: detectingan occurrence of a predetermined event that includes at least one of aconclusion of a page of a content item, a conclusion of a chapter or aconclusion of another predefined section of the content item, aninsertion of an annotation into the content item, or an expiration of anallotted amount of time; and wherein causing display of the customizedquestionnaire on the user device is further based at least in part onthe occurrence of the predetermined event.
 16. The computer-implementedmethod of claim 12, further comprising generating a recommendation basedat least in part on the user-driven index.
 17. A device comprising: oneor more processors; memory accessible by the one or more processors; andoperational logic stored in the memory and executable on the one or moreprocessors to perform actions comprising: causing, via a user interface,display of a portion of an electronic content item; detecting a userinteraction with the electronic content item; determining a rate ofabandonment of content items associated with an ambient light intensitythat is equal to or below a threshold value; determining, based at leastpartly on the indication, that a current ambient light intensityreceived by the device is at or below the threshold value; causing, viathe user interface, display of a customized questionnaire to solicit aresponse to at least one question based at least in part on theelectronic content item, the at least one question being associated withan abandonment of the electronic content item; receiving the response;transmitting the response for incorporation to a user-driven index; andcausing, via the user interface, display of a recommendation for atleast one activity associated with the response.
 18. The device of claim17, wherein the portion of the electronic content item comprises one ormore of pages of the electronic content item, chapters of the electroniccontent item, episodes of the electronic content item, tracks of theelectronic content item, or scenes of the electronic content item. 19.The device of claim 17, wherein the electronic content item comprisesone or more of books, magazines, periodicals, photographs, audio, video,or music.
 20. The device of claim 17, wherein the operational logic isfurther executable by the one or more processors to perform actionscomprising: detecting an occurrence of one or more of a conclusion of apage, chapter, episode, track, scene, or other predefined section of theelectronic content item, or expiration of an allotted amount of time,and detecting a motion of the device at least partly after detecting theoccurrence.
 21. The device of claim 17, wherein the operational logic isfurther executable by the one or more processors to perform actionscomprising: detecting an occurrence of a plurality of electronic contentitems being organized on the device, and detecting a motion of thedevice at least partly after detecting the occurrence.
 22. The device ofclaim 17, wherein the at least one question solicits a recommendationfor similar items based at least in part on the electronic content item.23. The device of claim 17, wherein the at least one question solicitsinformation comprising one or more of category, subject, genre, style,format, or language of the electronic content item.
 24. Thecomputer-implemented method of claim 1, wherein the user device includesan ambient light sensor that measures the current ambient lightintensity.
 25. The computer-implemented method of claim 1, furthercomprising: generating a recommendation that includes at least one ormore services based at least in part on the electronic book and theresponse.
 26. The computer-implemented method of claim 1, wherein theuser device includes one or more accelerometers, and further comprising:determining, based at least partly on the indication, that a motion ofthe user device corresponds to walking, and wherein the differentcustomized questionnaire includes a recommendation for activitiesassociated with walking.
 27. The computer-implemented method of claim 1,wherein the indication of the user interaction is a first indication,and further comprising: receiving, via the user device, a secondindication of an annotation to be associated with a portion of theelectronic book, and wherein the customized questionnaire includes atleast one question that is associated with the portion of the electronicbook.
 28. The computer-implemented method of claim 7, furthercomprising: assessing the reading level of the electronic book based atleast in part on the response; and causing display of a recommendationof additional electronic content items based at least in part on thereading level.
 29. The computer-implemented method of claim 12, furthercomprising: determining a credibility score of a user associated withthe user device, the credibility score based at least in part on atleast one of a measurement of user interaction with the content item ora qualification associated with the user as an expert of subject matterassociated with the content item; and determining a review value basedat least in part on the credibility score, wherein generating the atleast one different question is further based at least in part on thereview value being greater than a predetermined threshold.
 30. Thedevice of claim 17, wherein the operational logic is further executableby the one or more processors to perform actions comprising: determiningthat an annotation is to be associated with a portion of the electroniccontent item, based at least in part on detecting the user interactionwith the electronic content item, and wherein the at least one questionof the customized questionnaire is further based at least in part on theannotation.
 31. The device of claim 17, wherein the operational logic isfurther executable by the one or more processors to perform actionscomprising: detecting an occurrence of a predetermined event associatedwith the user interaction with the electronic content item, thepredetermined event occurring after a purchase of the electronic contentitem, and wherein causing display of the customized questionnaire isfurther based at least in part on the occurrence of the predeterminedevent.
 32. The device of claim 17, wherein the electronic content itemis a first electronic content item, the response is a first response,the customized questionnaire is a first customized questionnaire, andwherein the operational logic is further executable by the one or moreprocessors to perform actions comprising: presenting a portion of asecond electronic content item for consumption, based at least in parton receiving the first response; and presenting a second customizedquestionnaire that includes at least one second question based at leastin part on the second electronic content item and the first response.33. The device of claim 17, wherein the recommendation is a firstrecommendation, and wherein the operational logic is further executableby the one or more processors to perform actions comprising: presentinga second recommendation of an additional electronic content item that issimilar to the electronic content item, the additional electroniccontent item including at least one of electronic books, periodicals,music, movies, photographs, audio files, or video files.